Metabolomics for early detection of drug-induced kidney injury: review of the current status

Renal toxicity of ifosfamide in children with cancer: an exploratory study integrating aldehyde dehydrogenase enzymatic activity data and a wide-array urinary metabolomics approach

BACKGROUND

Ifosfamide is a major anti-cancer drug in children with well-known renal toxicity. Understanding the mechanisms underlying this toxicity could help identify children at increased risk of toxicity.

METHODS

The IFOS01 study included children undergoing ifosfamide-based chemotherapy for Ewing sarcoma or rhabdomyosarcoma. A fully evaluation of renal function was performed during and after chemotherapy. Proton nuclear magnetic resonance (NMR) and conventional biochemistry were used to detect early signs of ifosfamide-induced tubulopathy. The enzymatic activity of aldehyde dehydrogenase (ALDH) was measured in the peripheral blood lymphocytes as a marker of ifosfamide-derived chloroacetaldehyde detoxification capacity. Plasma and urine concentrations of ifosfamide and dechloroethylated metabolites were quantified.

RESULTS

The 15 participants received a median total ifosfamide dose of 59 g/m2 (range: 24-102), given over a median of 7 cycles (range: 4-14). All children had acute proximal tubular toxicity during chemotherapy that was reversible post-cycle, seen with both conventional assays and NMR. After a median follow-up of 31 months, 8/13 children presented overall chronic toxicity among which 7 had decreased glomerular filtration rate. ALDH enzymatic activity showed high inter- and intra-individual variations across cycles, though overall activity looked lower in children who subsequently developed chronic nephrotoxicity. Concentrations of ifosfamide and metabolites were similar in all children.

CONCLUSIONS

Acute renal toxicity was frequent during chemotherapy and did not allow identification of children at risk for long-term toxicity. A role of ALDH in late renal dysfunction is possible so further exploration of its enzymatic activity and polymorphism should be encouraged to improve the understanding of ifosfamide-induced nephrotoxicity.

Protective effect of Clinacanthus nutans in cisplatin-induced nephrotoxicity on human kidney cell (PCS-400-010) elucidated by an LCMS-based metabolomics approach

Cisplatin-induced nephrotoxicity has been widely reported in numerous studies. The objective of this study is to assess the potential nephroprotective effects of Clinacanthus nutans (Burm. f.) Lindau (Acanthaceae) leaf extracts on human kidney cells (PCS-400-010) in vitro using an LCMS-based metabolomics approach. Orthogonal partial least square-discriminant analysis identified 16 significantly altered metabolites when comparing the control and pre-treated C. nutans cisplatin-induced groups. These metabolites were found to be associated with glycerophospholipid, purine, and amino acid metabolism, as well as the glycolysis pathway. Pre-treatment with C. nutans aqueous extract (125 μg/mL) for 24 h, followed by 48 h of cisplatin induction in PCS-400-010 cells, demonstrated a nephroprotective effect, particularly involving the regulation of amino acid metabolism.

The identification of key metabolites and mechanisms during isoniazid/rifampicin-induced neurotoxicity and hepatotoxicity in a mouse model by HPLC-TOF/MS-based untargeted urine metabolomics

The co-administration of isoniazid (INH) and rifampicin (RIF) is associated with hepatotoxicity and neurotoxicity. To systematically investigate the mechanisms of hepatotoxicity and neurotoxicity induced by INH/RIF, we used high performance liquid chromatography-time of flight mass spectrometry (HPLC-TOF/MS)-based untargeted metabolomics to analyze urine from a mouse model and screened a range of urinary biomarkers. Mice were orally co-administered with INH (120 mg/kg) and RIF (240 mg/kg) and urine samples were collected on days 0, 7, 14 and 21. Hepatotoxicity and neurotoxicity were assessed by samples of liver, brain and kidney tissue which were harvested for histological analysis. Toxicity analysis revealed that INH/RIF caused hepatotoxicity and neurotoxicity in a time-dependent manner; compared with day 0, the levels of 35, 82 and 86 urinary metabolites were significantly different on days 7, 14 and 21, respectively. Analysis showed that by day 21, exposure to INH+RIF had caused disruption in vitamin B6 metabolism; the biosynthesis of unsaturated fatty acids; tyrosine, taurine, hypotaurine metabolism; the synthesis of ubiquinone and other terpenoid-quinones; and the metabolism of tryptophan, nicotinate and nicotinamide. Nicotinic acid, nicotinuric acid and kynurenic acid were identified as sensitive urinary biomarkers that may be useful for the diagnosis and evaluation of toxicity.

Maternal Plasma Metabolic Profile Demarcates a Role for Neuroinflammation in Non-Typical Development of Children

Maternal and cord plasma metabolomics were used to elucidate biological pathways associated with increased diagnosis risk for autism spectrum disorders (ASD). Metabolome-wide associations were assessed in both maternal and umbilical cord plasma in relation to diagnoses of ASD and other non-typical development (Non-TD) compared to typical development (TD) in the Markers of Autism risk in Babies: Learning Early Signs (MARBLES) cohort study of children born to mothers who already have at least one child with ASD. Analyses were stratified by sample matrix type, machine mode, and annotation confidence level. Dimensionality reduction techniques were used [i.e, principal component analysis (PCA) and random subset weighted quantile sum regression (WQSRS)] to minimize the high multiple comparison burden. With WQSRS, a metabolite mixture obtained from the negative mode of maternal plasma decreased the odds of Non-TD compared to TD. These metabolites, all related to the prostaglandin pathway, underscored the relevance of neuroinflammation status. No other significant findings were observed. Dimensionality reduction strategies provided confirming evidence that a set of maternal plasma metabolites are important in distinguishing Non-TD compared to TD diagnosis. A lower risk for Non-TD was linked to anti-inflammatory elements, thereby linking neuroinflammation to detrimental brain function consistent with studies ranging from neurodevelopment to neurodegeneration.

PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation

Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used automated, machine-learning, high-dimensional data pruning, and validated identified biomarkers. The parent cohort consisted of male, never-smoking firefighters with WTC-LI (FEV_{1, %Pred}< lower limit of normal (LLN); n = 100) and controls (n = 127) and had their biomarkers assessed. Cases and controls (n = 15/group) underwent untargeted metabolomics, then feature selection performed on metabolites, cytokines, chemokines, and clinical data. Cytokines, chemokines, and clinical biomarkers were validated in the non-overlapping parent-cohort via binary logistic regression with 5-fold cross validation. Random forests of metabolites (n = 580), clinical biomarkers (n = 5), and previously assayed cytokines, chemokines (n = 106) identified that the top 5% of biomarkers important to class separation included pigment epithelium-derived factor (PEDF), macrophage derived chemokine (MDC), systolic blood pressure, macrophage inflammatory protein-4 (MIP-4), growth-regulated oncogene protein (GRO), monocyte chemoattractant protein-1 (MCP-1), apolipoprotein-AII (Apo-AII), cell membrane metabolites (sphingolipids, phospholipids), and branched-chain amino acids. Validated models via confounder-adjusted (age on 9/11, BMI, exposure, and pre-9/11 FEV_{1, %Pred}) binary logistic regression had AUC_ROC [0.90(0.84–0.96)]. Decreased PEDF and MIP-4, and increased Apo-AII were associated with increased odds of WTC-LI. Increased GRO, MCP-1, and simultaneously decreased MDC were associated with decreased odds of WTC-LI. In conclusion, automated data pruning identified novel WTC-LI biomarkers; performance was validated in an independent cohort. One biomarker—PEDF, an antiangiogenic agent—is a novel, predictive biomarker of particulate-matter-related lung disease. Other biomarkers—GRO, MCP-1, MDC, MIP-4—reveal immune cell involvement in WTC-LI pathogenesis. Findings of our automated biomarker identification warrant further investigation into these potential pharmacotherapy targets.

Disease related to air pollution causes millions of deaths annually. Large swathes of the general population, as well as certain occupations such as 1^st responders and military personnel, are exposed to particulate matter (PM)—a major component of air pollution. Our longitudinal cohort of FDNY firefighters exposed to the World Trade Center dust cloud on 9/11 is a unique research opportunity to characterize the impact of a single, intense PM exposure by looking at pre- and post-exposure phenotype; however, PM-related lung disease and PM’s systemic effects are complex and call for a systems biological approach coupled with novel computational modelling techniques to fully understand pathogenesis. In the present study, we integrate clinical and environmental biomarkers with the serum metabolome, cytokines, and chemokines to develop a model for early disease detection and identification of potential signaling cascades of PM-related chronic lung disease.

Metabolome and microbiome in kidney diseases

Despite several decades of intensive research and hard work in nephrology, a void exists in the availability of markers for identifying at-risk individuals, diagnosing diseases at incipient stage, and predicting treatment response. Most of the current widely available diagnostic tools such as creatinine, urine analysis, and imaging studies are quite insensitive such that about half of the kidney function is lost before perceivable changes are observed with these tests. In addition, these parameters are affected by factors other than renal, questioning their specificity. Renal biopsy, though specific, is quite expensive, risky, and invasive. The recent surge in the knowledge of small molecules in the tissue and body fluids, "metabolomics," thanks to the Human Metabolome Database created by the Human Metabolome Project, has opened a new avenue for better understanding the disease pathogenesis and, in parallel, to identify novel biomarkers and druggable targets. Kidney, by virtue of its metabolic machinery and also being a major handler of metabolites generated by other tissues, is very much amenable to the metabolomic approach of studying its various perturbations. The gut microbiome, characterized by the Human Microbiome Project, is one of the principal players in metabolomics. Changes in metabolite profile due to alterations in gut microbiome can occur either as a cause or consequence of renal diseases. Unmasking the renal-metabolome-microbiome link has a great potential to script a new era in the diagnosis and management of renal diseases.

Biomarkers of Acute and Chronic Kidney Disease

The current unidimensional paradigm of kidney disease detection is incompatible with the complexity and heterogeneity of renal pathology. The diagnosis of kidney disease has largely focused on glomerular filtration, while assessment of kidney tubular health has notably been absent. Following insult, the kidney tubular cells undergo a cascade of cellular responses that result in the production and accumulation of low-molecular-weight proteins in the urine and systemic circulation. Modern advancements in molecular analysis and proteomics have allowed the identification and quantification of these proteins as biomarkers for assessing and characterizing kidney diseases. In this review, we highlight promising biomarkers of kidney tubular health that have strong underpinnings in the pathophysiology of kidney disease. These biomarkers have been applied to various specific clinical settings from the spectrum of acute to chronic kidney diseases, demonstrating the potential to improve patient care.

Genome-Scale Model-Based Identification of Metabolite Indicators for Early Detection of Kidney Toxicity

Identifying early indicators of toxicant-induced organ damage is critical to provide effective treatment. To discover such indicators and the underlying mechanisms of toxicity, we used gentamicin as an exemplar kidney toxicant and performed systematic perturbation studies in Sprague Dawley rats. We obtained high-throughput data 7 and 13 h after administration of a single dose of gentamicin (0.5 g/kg) and identified global changes in genes in the liver and kidneys, metabolites in the plasma and urine, and absolute fluxes in central carbon metabolism. We used these measured changes in genes in the liver and kidney as constraints to a rat multitissue genome-scale metabolic network model to investigate the mechanism of gentamicin-induced kidney toxicity and identify metabolites associated with changes in tissue gene expression. Our experimental analysis revealed that gentamicin-induced metabolic perturbations could be detected as early as 7 h postexposure. Our integrated systems-level analyses suggest that changes in kidney gene expression drive most of the significant metabolite alterations in the urine. The analyses thus allowed us to identify several significantly enriched injury-specific pathways in the kidney underlying gentamicin-induced toxicity, as well as metabolites in these pathways that could serve as potential early indicators of kidney damage.

Toxicity and Its Mechanism Study of Arecae semen Aqueous Extract in Wistar Rats by UPLC-HDMS-Based Serum Metabolomics

Background

Arecae semen (AS) is officially recorded in Chinese Pharmacopoeia and it is known for its multiple functions, including antidepressive, antioxidant, anti-inflammatory, and cholesterol-lowering effects, which have been confirmed by modern pharmacological study. Previous study in our laboratory showed that long-term oral administration of Arecae semen (AS) is officially recorded in Chinese Pharmacopoeia and it is known for its multiple functions, including antidepressive, antioxidant, anti-inflammatory, and cholesterol-lowering effects, which have been confirmed by modern pharmacological study. Previous study in our laboratory showed that long-term oral administration of Hypothesis. The aim of this work was to characterize the metabolome, evaluate the metabolic changes, and study the mechanisms of the toxicity induced by different treatment doses of ASAE via metabolomics.

Methods

Wistar rats were administered orally two different doses of ASAE (1500 and 4500 mg/kg/d) for 30 days. The investigation was carried out to evaluate the safety of ASAE. And, the UPLC-HDMS-based serum metabolomics in conjunction with multivariate statistical techniques was applied to investigate the serum metabolite profile and potential markers of toxicity induced by different doses of ASAE.

Results

Coupled with blood biochemistry and histopathology results, the significant difference in metabolic profiling was observed between 1500 and 4500 mg/kg/d dosages of ASAE-treated rats and normal rats by using pattern recognition analysis, indicating that changes in serum metabolites must have occurred. Some significant changed metabolites such as arachidonic acid, linoleic acid, stearic acid, and LPC (18 : 1) have been found and identified. These biochemical changes in serum metabolites are related to the perturbation of linoleic acid metabolism, arachidonic acid metabolism, glycerophospholipid metabolism, and purine metabolism, which may be helpful to further understand the cardiotoxicity and neurotoxicity of ASAE.

Conclusion

The study shows that the metabolomic method may be a valuable tool for studying the essence of toxicity induced by traditional Chinese medicine.

Assessing the Protective Metabolome Using Machine Learning in World Trade Center Particulate Exposed Firefighters at Risk for Lung Injury

The metabolome of World Trade Center (WTC) particulate matter (PM) exposure has yet to be fully defined and may yield information that will further define bioactive pathways relevant to lung injury. A subset of Fire Department of New York firefighters demonstrated resistance to subsequent loss of lung function. We intend to characterize the metabolome of never smoking WTC-exposed firefighters, stratified by resistance to WTC-Lung Injury (WTC-LI) to determine metabolite pathways significant in subjects resistant to the loss of lung function. The global serum metabolome was determined in those resistant to WTC-LI and controls (n = 15 in each). Metabolites most important to class separation (top 5% by Random Forest (RF) of 594 qualified metabolites) included elevated amino acid and long-chain fatty acid metabolites, and reduced hexose monophosphate shunt metabolites in the resistant cohort. RF using the refined metabolic profile was able to classify cases and controls with an estimated success rate of 93.3%, and performed similarly upon cross-validation. Agglomerative hierarchical clustering identified potential influential pathways of resistance to the development of WTC-LI. These pathways represent potential therapeutic targets and warrant further research.

Urinary metabolites predict prolonged duration of delayed graft function in DCD kidney transplant recipients

Extending kidney donor criteria, including donation after circulatory death (DCD), has resulted in increased rates of delayed graft function (DGF) and primary nonfunction. Here, we used Nuclear Magnetic Resonance (NMR) spectroscopy to analyze the urinary metabolome of DCD transplant recipients at multiple time points (days 10, 42, 180, and 360 after transplantation). The aim was to identify markers that predict prolonged duration of functional DGF (fDGF). Forty-seven metabolites were quantified and their levels were evaluated in relation to fDGF. Samples obtained at day 10 had a different profile than samples obtained at the other time points. Furthermore, at day 10 there was a statistically significant increase in eight metabolites and a decrease in six metabolites in the group with fDGF (N = 53) vis-à-vis the group without fDGF (N = 22). In those with prolonged fDGF (≥21 days) (N = 17) urine lactate was significantly higher and pyroglutamate lower than in those with limited fDGF (<21 days) (N = 36). In order to further distinguish prolonged fDGF from limited fDGF, the ratios of all metabolites were analyzed. In a logistic regression analysis, the sum of branched-chain amino acids (BCAAs) over pyroglutamate and lactate over fumarate, predicted prolonged fDGF with an AUC of 0.85. In conclusion, kidney transplant recipients with fDGF can be identified based on their altered urinary metabolome. Furthermore, two ratios of urinary metabolites, lactate/fumarate and BCAAs/pyroglutamate, adequately predict prolonged duration of fDGF.

Metabolomics of World Trade Center-Lung Injury: a machine learning approach

Introduction

Biomarkers of metabolic syndrome expressed soon after World Trade Center (WTC) exposure predict development of WTC Lung Injury (WTC-LI). The metabolome remains an untapped resource with potential to comprehensively characterise many aspects of WTC-LI. This case–control study identified a clinically relevant, robust subset of metabolic contributors of WTC-LI through comprehensive high-dimensional metabolic profiling and integration of machine learning techniques.

Methods

Never-smoking, male, WTC-exposed firefighters with normal pre-9/11 lung function were segregated by post-9/11 lung function. Cases of WTC-LI (forced expiratory volume in 1s <lower limit of normal, n=15) and controls (n=15) were identified from previous cohorts. The metabolome of serum drawn within 6 months of 9/11 was quantified. Machine learning was used for dimension reduction to identify metabolites associated with WTC-LI.

Results

580 metabolites qualified for random forests (RF) analysis to identify a refined metabolite profile that yielded maximal class separation. RF of the refined profile correctly classified subjects with a 93.3% estimated success rate. 5 clusters of metabolites emerged within the refined profile. Prominent subpathways include known mediators of lung disease such as sphingolipids (elevated in cases of WTC-LI), and branched-chain amino acids (reduced in cases of WTC-LI). Principal component analysis of the refined profile explained 68.3% of variance in five components, demonstrating class separation.

Conclusion

Analysis of the metabolome of WTC-exposed 9/11 rescue workers has identified biologically plausible pathways associated with loss of lung function. Since metabolites are proximal markers of disease processes, metabolites could capture the complexity of past exposures and better inform treatment. These pathways warrant further mechanistic research.

Targeting human urinary metabolome by LC-MS/MS: a review

Urine is a biological matrix that contains hundreds of metabolic end products which constitute the urinary metabolome. The development and advances on LC-MS/MS have revolutionized the analytical study of biomolecules by enabling their accurate identification and quantification in an unprecedented manner. Nowadays, LC-MS/MS is helping to unveil the complexity of urine metabolome, and the results obtained have multiple biomedical applications. This review focuses on the targeted LC-MS/MS analysis of the urine metabolome. In the first part, we describe general considerations (from sample collection to quantitation) required for a proper targeted metabolic analysis. In the second part, we address the urinary analysis and recent applications of four relevant families: amino acids, catecholamines, lipids and steroids.

Metabolomics as a tool to evaluate the toxicity of formulations containing amphotericin B, an antileishmanial drug

Amphotericin B (AmB) is a drug of choice against life-threatening systemic fungal infections and an alternative therapy for the treatment of all forms of leishmaniasis. It is known that AmB and its conventional formulation cause renal damage; however, the lipid formulations can reduce these effects. The aim of the present study was to identify metabolic changes in mice treated with two different AmB formulations, a nanoemulsion (NE) (lipid system carrier) loaded with AmB and the conventional formulation (C-AmB). For this purpose, metabolic fingerprinting represents a valuable strategy to monitor, in a non-targeted manner, the changes that are at the base of the toxicity mechanism of AmB. Plasma samples of BALB-c mice were collected after treatment with 3 alternate doses of AmB at 1 mg kg-1 administered intravenously and analysed with CE, LC and GC coupled to MS. Blood urea nitrogen (BUN) and plasma creatinine levels were also analysed. Kidney tissue specimens were collected and evaluated. It was not observed that there were any alterations in BUN and creatinine levels as well as in histopathological analysis. Approximately 30 metabolites were identified as potentially related to early C-AmB-induced nephrotoxicity. Disturbances in the arachidonic acid, glycerophospholipid, acylcarnitine and polyunsaturated fatty acid (PUFA) pathways were observed in C-AmB-treated mice. In the AmB-loaded NE group, it was observed that there were fewer metabolic changes, including changes in the plasma levels of cortisol and pyranose. The candidate biomarkers revealed in this study could be useful in the detection of the onset and severity of kidney injury induced by AmB formulations.

Plasma metabolic profile delineates roles for neurodegeneration, pro-inflammatory damage and mitochondrial dysfunction in the FMR1 premutation

Carriers of premutation CGG expansions in the fragile X mental retardation 1 (FMR1) gene are at higher risk of developing a late-onset neurodegenerative disorder named Fragile X-associated tremor ataxia syndrome (FXTAS). Given that mitochondrial dysfunction has been identified in fibroblasts, PBMC and brain samples from carriers as well as in animal models of the premutation and that mitochondria are at the center of intermediary metabolism, the aim of the present study was to provide a complete view of the metabolic pattern by uncovering plasma metabolic perturbations in premutation carriers. To this end, metabolic profiles were evaluated in plasma from 23 premutation individuals and 16 age- and sex-matched controls. Among the affected pathways, mitochondrial dysfunction was associated with a Warburg-like shift with increases in lactate levels and altered Krebs' intermediates, neurotransmitters, markers of neurodegeneration and increases in oxidative stress-mediated damage to biomolecules. The number of CGG repeats correlated with a subset of plasma metabolites, which are implicated not only in mitochondrial disorders but also in other neurological diseases, such as Parkinson's, Alzheimer's and Huntington's diseases. For the first time, the identified pathways shed light on disease mechanisms contributing to morbidity of the premutation, with the potential of assessing metabolites in longitudinal studies as indicators of morbidity or disease progression, especially at the early preclinical stages.

Plasma Biomarkers for Monitoring Brain Pathophysiology in FMR1 Premutation Carriers

Premutation carriers have a 55–200 CGG expansion in the fragile X mental retardation 1 (FMR1) gene. Currently, 1.5 million individuals are affected in the United States, and carriers are at risk of developing the late-onset neurodegenerative disorder Fragile X-associated tremor ataxia syndrome (FXTAS). Limited efforts have been made to develop new methods for improved early patient monitoring, treatment response, and disease progression. To this end, plasma metabolomic phenotyping was obtained for 23 premutation carriers and 16 age- and sex-matched controls. Three biomarkers, phenylethylamine normalized by either aconitate or isocitrate and oleamide normalized by isocitrate, exhibited excellent model performance. The lower phenylethylamine and oleamide plasma levels in carriers may indicate, respectively, incipient nigrostriatal degeneration and higher incidence of substance abuse, anxiety and sleep disturbances. Higher levels of citrate, isocitrate, aconitate, and lactate may reflect deficits in both bioenergetics and neurotransmitter metabolism (Glu, GABA). This study lays important groundwork by defining the potential utility of plasma metabolic profiling to monitor brain pathophysiology in carriers before and during the progression of FXTAS, treatment efficacy and evaluation of side effects.

Toxic Markers of Matrine Determined Using (1) H-NMR-Based Metabolomics in Cultured Cells In Vitro and Rats In Vivo

Matrine is one of the main bioactive alkaloids of Sophora flavescens Aiton, which has been widely used to treat various diseases in China. These diseases include viral hepatitis, liver fibrosis, cardiac arrhythmia, skin diseases, and tumors. However, matrine is also the main toxic compound of this herb, and the available biomarkers are not reliable in detecting or quantifying matrine risk. Metabolomics is a powerful tool used to identify early toxicity biomarkers that are specific indicators of damage to biosystems. This study aimed to find the potential biomarkers of the matrine-induced toxic effects in rats and HepG2 cells. The toxicological effects of rats induced by matrine could be derived from the elevated taurine and trimethylamine N-oxide levels and the depletion in hippurate and tricarboxylic acid cycle intermediates, such as 2-oxoglutarate, citrate, and succinate in the urine. Cell metabolomics revealed that the levels of alanine, choline, glutathione, lactate, phosphocholine, and cholesterol showed dose-dependent decreases, whereas the levels of taurine, fatty acid, and unsaturated fatty acid showed dose-dependent increases. Overall, a significant perturbation of metabolites in response to high dose of matrine was observed both in vivo and in vitro, and the selected metabolites particularly represent an attractive marker for matrine-induced toxicity.

Transgenic mice and metabolomics for study of hepatic xenobiotic metabolism and toxicity

INTRODUCTION

The study of xenobiotic metabolism and toxicity has been greatly aided by the use of genetically modified mouse models and metabolomics.

AREAS COVERED

Gene knockout mice can be used to determine the enzymes responsible for the metabolism of xenobiotics in vivo and to examine the mechanisms of xenobiotic-induced toxicity. Humanized mouse models are especially important because there exist marked species differences in the xenobiotic-metabolizing enzymes and the nuclear receptors that regulate these enzymes. Humanized mice expressing CYPs and nuclear receptors including the pregnane X receptor, the major regulator of xenobiotic metabolism and transport were produced. With genetically modified mouse models, metabolomics can determine the metabolic map of many xenobiotics with a level of sensitivity that allows the discovery of even minor metabolites. This technology can be used for determining the mechanism of xenobiotic toxicity and to find early biomarkers for toxicity.

EXPERT OPINION

Metabolomics and genetically modified mouse models can be used for the study of xenobiotic metabolism and toxicity by: i) comparison of the metabolomics profiles between wild-type and genetically modified mice, and searching for genotype-dependent endogenous metabolites; ii) searching for and elucidating metabolites derived from xenobiotics; and iii) discovery of specific alterations of endogenous compounds induced by xenobiotics-induced toxicity.

Normalization to specific gravity prior to analysis improves information recovery from high resolution mass spectrometry metabolomic profiles of human urine

Extraction of meaningful biological information from urinary metabolomic profiles obtained by liquid-chromatography coupled to mass spectrometry (MS) necessitates the control of unwanted sources of variability associated with large differences in urine sample concentrations. Different methods of normalization either before analysis (preacquisition normalization) through dilution of urine samples to the lowest specific gravity measured by refractometry, or after analysis (postacquisition normalization) to urine volume, specific gravity and median fold change are compared for their capacity to recover lead metabolites for a potential future use as dietary biomarkers. Twenty-four urine samples of 19 subjects from the European Prospective Investigation into Cancer and nutrition (EPIC) cohort were selected based on their high and low/nonconsumption of six polyphenol-rich foods as assessed with a 24 h dietary recall. MS features selected on the basis of minimum discriminant selection criteria were related to each dietary item by means of orthogonal partial least-squares discriminant analysis models. Normalization methods ranked in the following decreasing order when comparing the number of total discriminant MS features recovered to that obtained in the absence of normalization: preacquisition normalization to specific gravity (4.2-fold), postacquisition normalization to specific gravity (2.3-fold), postacquisition median fold change normalization (1.8-fold increase), postacquisition normalization to urinary volume (0.79-fold). A preventative preacquisition normalization based on urine specific gravity was found to be superior to all curative postacquisition normalization methods tested for discovery of MS features discriminant of dietary intake in these urinary metabolomic datasets.

Academic College of Emergency Experts in India's INDO-US Joint Working Group and OPUS12 Foundation Consensus Statement on Creating A Coordinated, Multi-Disciplinary, Patient-Centered, Global Point-of-Care Biomarker Discovery Network

Biomarker science brings great promise to clinical medicine. This is especially true in the era of technology miniaturization, rapid dissemination of knowledge, and point-of-care (POC) implementation of novel diagnostics. Despite this tremendous progress, the journey from a candidate biomarker to a scientifically validated biomarker continues to be an arduous one. In addition to substantial financial resources, biomarker research requires considerable expertise and a multidisciplinary approach. Investigational designs must also be taken into account, with the randomized controlled trial remaining the “gold standard”. The authors present a condensed overview of biomarker science and associated investigational methods, followed by specific examples from clinical areas where biomarker development and/or implementation resulted in tangible enhancements in patient care. This manuscript also serves as a call to arms for the establishment of a truly global, well-coordinated infrastructure dedicated to biomarker research and development, with focus on delivery of the latest discoveries directly to the patient via point-of-care technology.

Metabolomics in nephrotoxicity

Nephrotoxicity or renal toxicity can be a result of hemodynamic changes, direct injury to cells and tissue, inflammatory tissue injury, and/or obstruction of renal excretion. Nephrotoxicity is frequently induced by a wide spectrum of therapeutic drugs and environ mental pollutants. Knowledge of the complex molecular and pathophysiologic mechanisms leading to nephrotoxicity remains limited, in part, by research that historically focused on single or relatively few risk markers. As such, current kidney injury biomarkers are inadequate in terms of sensitivity and specificity. In contrast, metabolomics enables screening of a vast array of metabolites simultaneously using NMR and MS to assess their role in nephrotoxicity development and progression. A more comprehensive understanding of these biochemical pathways would also provide valuable insight to disease mechanisms critical for drug development and treatment.

Identification of metabolomic biomarkers for drug-induced acute kidney injury in rats

Nephrotoxicity is a common side effect observed during both nonclinical and clinical drug development investigations. The present study aimed to identify metabolomic biomarkers that could provide early and sensitive indication of nephrotoxicity in rats. Metabolomic analyses were performed using capillary electrophoresis-time-of-flight mass spectrometry on rat plasma collected at 9 and 24 h after a single dose of 2-bromoethylamine or n-phenylanthranilic acid and at 24 h after 7 days of repeated doses of gentamicin, cyclosporine A or cisplatin. Among a total of 169 metabolites identified, 3-methylhistidine (3-MH), 3-indoxyl sulfate (3-IS) and guanidoacetate (GAA) were selected as candidate biomarkers. The biological significance and reproducibility of the observed changes were monitored over time in acute nephrotoxicity model rats treated with a single dose of cisplatin, with the glomerular filtration rate monitored by determination of creatinine clearance. Increased plasma levels of 3-MH and 3-IS were related to a decline in glomerular filtration due to a renal failure. In contrast, the decrease in plasma GAA, which is synthesized from arginine and glycine in the kidneys, was considered to reflect decreased production due to renal malfunction. Although definitive validation studies are required to confirm their usefulness and reliability, 3-MH, 3-IS and GAA may prove to be valuable plasma biomarkers for monitoring nephrotoxicity in rats.

Urinary metabonomic study of the surface layer of Poria cocos as an effective treatment for chronic renal injury in rats

ETHNOPHARMACOLOGICAL RELEVANCE

Poria cocos Wolf (Polyporaceae) is a well-known medicinal fungus. The epidermis of the sclerotia ("Fu-Ling-Pi" in Chinese) is used as a diuretic and traditionally used for promoting urination and reduce edema.

AIM OF THE STUDY

Traditional Chinese medicines (TCM) treat many diseases through multi-components, multi-ways and multi-targets. However, the molecular mechanisms of TCM are not yet well understood. In the present work, ultra performance liquid chromatography-based metabonomics analysis was applied to investigate the urinary metabolite profiling of the renoprotective effect of FLP on adenine-induced chronic kidney disease (CKD) rat model and involved possible mechanism.

MATERIAL AND METHODS

A metabonomic approach based on ultra performance liquid chromatography coupled with quadrupole time-of-flight high-sensitivity mass spectrometry and a novel mass spectrometry(Elevated Energy) data collection technique was developed. The resulting dataset was analyzed by principal component analysis and partial least squares discriminant analysis. The identification of all potential biomarkers was performed using reference standard by comparing their mass spectra, MS(E) fragments information, isotopic pattern and MassLynx i-FIT algorithm.

RESULTS

By partial least squares-discriminate analysis, 15 biomarkers in rat urine were identified and 11 of them were related to the pathway of adenine metabolism and amino acid metabolism. Among these biomarkers, eight biomarkers like adenine, L-acetylcarnitine, 8-hydroxyadenine, hypoxanthine, creatine, methionine, phytosphingosine and phenylalanine were reversed to the control level in FLP-treated group and six biomarkers like 2,8-dihydroxyadenine, indole-3-carboxylic acid, 3-methyldioxyindole, ethyl-N2-acetyl-L-argininate, 3-O-methyldopa and xanthurenic acid were reversed to high control group by FLP, which indicates that the urinary metabolic pattern significantly changed after FLP treatment.

CONCLUSIONS

Our study indicates that FLP treatment can ameliorate CKD by intervening in some dominating metabolic pathways, such as adenine metabolism and amino acid metabolism. The metabonomic results not only supplied a systematic view of the development and progression of CKD and mechanism studies of FLP but also provided the theoretical basis for the prevention or treatment of CKD.

Implementation of novel biomarkers in the diagnosis, prognosis, and management of acute kidney injury: executive summary from the tenth consensus conference of the Acute Dialysis Quality Initiative (ADQI)

Detection of acute kidney injury is undergoing a dynamic revolution of biomarker technology allowing greater, earlier, and more accurate determination of diagnosis, prognosis, and with powerful implication for management. Biomarkers can be broadly considered as any measurable biologic entity or process that allows differentiation between normal function and injury or disease. The ADQI (Acute Dialysis Quality Initiative) had its Ninth Consensus Conference dedicated to synthesis and formulation of the existing literature on biomarkers for the detection of acute kidney injury in a variety of settings. In the papers that accompany this summary, ADQI workgroups fully develop key concepts from a summary of the literature in the domains of early diagnosis, differential diagnosis, prognosis and management, and concurrent physiologic and imaging measures.

Metabolic profiling of the protozoan parasite Entamoeba invadens revealed activation of unpredicted pathway during encystation

Encystation, which is cellular differentiation from the motile, proliferative, labile trophozoite form to the dormant, resistant cyst form, is a crucial process found in parasitic and free-living protozoa such as Entamoeba, Giardia, Acanthamoeba, and Balamuthia. Since encystation is an essential process to deal with the adverse external environmental changes during the life cycle, and often integral to the transmission of the diseases, biochemical understanding of the process potentially provides useful measures against the infections caused by this group of protozoa. In this study, we investigated metabolic and transcriptomic changes that occur during encystation in Entamoeba invadens, the reptilian sibling of mammal-infecting E. histolytica, using capillary electrophoresis-tandem mass spectrometry-based metabolite profiling and DNA microarray-based expression profiling. As the encystation progressed, the levels of majority of metabolites involved in glycolysis and nucleotides drastically decreased, indicating energy generation is ceased. Furthermore, the flux of glycolysis was redirected toward chitin wall biosynthesis. We found remarkable temporal increases in biogenic amines such as isoamylamine, isobutylamine, and cadaverine, during the early period of encystation, when the trophozoites form large multicellular aggregates (precyst). We also found remarkable induction of γ-aminobutyric acid (GABA) during encystation. This study has unveiled for the first time the dynamics of the transcriptional and metabolic regulatory networks during encystation, and should help in better understanding of the process in pathogenic eukaryotes, and further development of measures controlling infections they cause.

Marking renal injury: can we move beyond serum creatinine?

Acute kidney injury (AKI) is a prevalent and devastating condition associated with significant morbidity and mortality. Despite marked improvements in clinical care, the outcomes for subjects with AKI have shown limited improvement in the past 50 years. A major factor inhibiting clinical progress in this field has been the inability to accurately predict and diagnose early kidney dysfunction. The current gold standard clinical and biochemical criteria for diagnosis of AKI, Risk Injury Failure Loss End-stage renal disease, and its modification, Acute Kidney Injury Network criteria, rely on urine output and serum creatinine, which are insensitive, nonspecific, and late markers of disease. The recent development of a variety of analytic mass spectrometry-based platforms have enabled separation, characterization, detection, and quantification of proteins (proteomics) and metabolites (metabolomics). These high-throughput platforms have raised hopes of identifying novel protein and metabolite markers, and recent efforts have led to several promising novel markers of AKI. However, substantial challenges remain, including the need to systematically evaluate incremental performance of these markers over and beyond current clinical and biochemical criteria for AKI. We discuss the basic issues surrounding AKI biomarker development, highlight the most promising markers currently under development, and discuss the barriers toward widespread clinical implementation of these markers.

Analytical metabolomics: nutritional opportunities for personalized health

Nutrition is the cornerstone of health; survival depends on acquiring essential nutrients, and dietary components can both prevent and promote disease. Metabolomics, the study of all small molecule metabolic products in a system, has been shown to provide a detailed snapshot of the body's processes at any particular point in time, opening up the possibility of monitoring health and disease, prevention and treatment. Metabolomics has the potential to fundamentally change clinical chemistry and, by extension, the fields of nutrition, toxicology and medicine. Technological advances, combined with new knowledge of the human genome and gut microbiome, have made and will continue to make possible earlier, more accurate, less invasive diagnoses, all while enhancing our understanding of the root causes of disease and leading to a generation of dietary recommendations that enable optimal health. This article reviews the recent contributions of metabolomics to the fields of nutrition, toxicology and medicine. It is expected that these fields will eventually blend together through development of new technologies in metabolomics and genomics into a new area of clinical chemistry: personalized medicine.

Urinary metabolomics in newborns and infants

Metabolomics is a new approach based on the systematic study of the full complement of metabolites in a biological sample. This technology consists of two sequential steps: (1) an experimental technique, based on nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry, designed to profile low-molecular-weight compounds, and (2) multivariate data analysis. The metabolomic analysis of biofluids or tissues has been successfully used in the fields of physiology, diagnostics, functional genomics, pharmacology, toxicology, and nutrition. Recent studies have evaluated how physiological variables or pathological conditions can affect metabolomic profiles of different biofluids in pediatric populations. The overall metabolic status of the neonate is little known. If more information on perinatal/neonatal maturational processes and their metabolic background were available, the management of sick or preterm newborns might be improved. Currently, the use of metabolomics in neonatology is still in the pioneering phase. Meaningful diagnostic information and simple, noninvasive collection techniques make urine a particularly suitable biofluid for metabolomic approach in neonatal medicine, although blood has also been investigated. Different fields of neonatology such as postnatal maturation, asphyxia/hypoxia, inborn errors of metabolism, nutrition, nephrouropathies, nephrotoxicity, cardiovascular diseases, and other conditions have been investigated using a metabolomic approach. Together with genomics and proteomics, metabolomics appears to be a promising tool in neonatology for the monitoring of postnatal metabolic maturation, the identification of biomarkers as early predictors of outcome, the diagnosis and monitoring of various diseases, and the "tailored" management of neonatal disorders.

Urinary metabonomics study on biochemical changes in an experimental model of chronic renal failure by adenine based on UPLC Q-TOF/MS

BACKGROUND

Chronic renal failure (CRF) is a serious clinical symptom, occurring as the end result of all kinds of chronic kidney disease and its pathophysiological mechanism is not yet well understood. We investigated the metabolic profiling of urine samples from CRF model rats to find potential disease biomarkers and research pathology of CRF.

METHODS

An animal model of CRF was produced by adenine. Metabolic profiling of the urine was performed by using ultra performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS). Acquired data were subjected to principal component analysis (PCA) for differentiating the CRF and the normal control groups. Potential biomarkers were screened by using S-plot and were identified by the accurate mass, isotopic pattern and MS(E) fragments information obtained from UPLC Q-TOF/MS analysis.

RESULTS

12 metabolites in urine were identified as potential biomarkers. Adenine-induced CRF rats were characterized by the increase of phytosphingosine, adrenosterone, tryptophan, 2,8-dihydroxyadenine, creatinine, and dihydrosphingosine together with the decrease of N-acetylleucine, 3-O-methyldopa, ethyl-N2-acetyl-L-argininate, dopamine, phenylalanine and kynurenic acid in urine. The altered metabolites demonstrated perturbations of amino acids metabolism, phospholipids metabolism and creatinine metabolism in CRF rats.

CONCLUSION

This work shows that metabonomics method is a valuable tool in CRF mechanism study and assists in clinical diagnosis of CRF.

Identification of urinary metabolites that distinguish membranous lupus nephritis from proliferative lupus nephritis and focal segmental glomerulosclerosis

Introduction

Systemic lupus erythematosus (SLE or lupus) is a chronic autoimmune disease, and kidney involvement with SLE, a.k.a. lupus nephritis (LN), is a frequent and severe complication of SLE that increases patient morbidity and mortality. About 50% of patients with SLE encounter renal abnormalities which, if left untreated, can lead to end-stage renal disease. Kidney biopsy is considered the criterion standard for diagnosis and staging of LN using the International Society of Nephrology/Renal Pathology Society (ISN/RPS) classification, which was developed to help predict renal outcomes and assist with medical decision-making. However, kidney biopsy-based classification of LN is highly invasive and impractical for real-time monitoring of LN status. Here, nuclear magnetic resonance (NMR) spectroscopy-based metabolic profiling was used to identify urinary metabolites that discriminated between proliferative and pure membranous LN as defined by the ISN/RPS classification, and between LN and primary focal segmental glomerulosclerosis (FSGS).

Methods

Metabolic profiling was conducted using urine samples of patients with proliferative LN without membranous features (Class III/IV; n = 7) or pure membranous LN (Class V; n = 7). Patients with primary FSGS and proteinuria (n = 10) served as disease controls. For each patient, demographic information and clinical data was obtained and a random urine sample collected to measure NMR spectra. Data and sample collection for patients with LN occurred around the time of kidney biopsy. Metabolic profiling analysis was done by visual inspection and principal component analysis.

Results

Urinary citrate levels were 8-fold lower in Class V LN compared to Class III/IV patients, who had normal levels of urinary citrate (P < 0.05). Class III/IV LN patients had > 10-fold lower levels of urinary taurine compared to Class V patients, who had mostly normal levels (P < 0.01). Class V LN patients had normal urinary hippurate levels compared to FSGS patients, who completely lacked urinary hippurate (P < 0.001).

Conclusions

This pilot study indicated differences in urinary metabolites between proliferative LN and pure membranous LN patients, and between LN and FSGS patients. If confirmed in larger studies, these urine metabolites may serve as biomarkers to help discriminate between different classes of LN, and between LN and FSGS.

Toxicogenomics and metabolomics of pentamethylchromanol (PMCol)-induced hepatotoxicity

Pentamethyl-6-chromanol (PMCol), a chromanol-type compound related to vitamin E, was proposed as an anticancer agent with activity against androgen-dependent cancers. In repeat dose-toxicity studies in rats and dogs, PMCol caused hepatotoxicity, nephrotoxicity, and hematological effects. The objectives of this study were to determine the mechanisms of the observed toxicity and identify sensitive early markers of target organ injury by integrating classical toxicology, toxicogenomics, and metabolomic approaches. PMCol was administered orally to male Sprague-Dawley rats at 200 and 2000 mg/kg daily for 7 or 28 days. Changes in clinical chemistry included elevated alanine aminotransferase, total bilirubin, cholesterol and triglycerides-indicative of liver toxicity that was confirmed by microscopic findings (periportal hepatocellular hydropic degeneration and cytomegaly) in treated rats. Metabolomic evaluations of liver revealed time- and dose-dependent changes, including depletion of total glutathione and glutathione conjugates, decreased methionine, and increased S-adenosylhomocysteine, cysteine, and cystine. PMCol treatment also decreased cofactor levels, namely, FAD and increased NAD(P)+. Microarray analysis of liver found that differentially expressed genes were enriched in the glutathione and cytochrome P450 pathways by PMCol treatment. Reverse transcription-polymerase chain reaction of six upregulated genes and one downregulated gene confirmed the microarray results. In conclusion, the use of metabolomics and toxicogenomics demonstrates that chronic exposure to high doses of PMCol induces liver damage and dysfunction, probably due to both direct inhibition of glutathione synthesis and modification of drug metabolism pathways. Depletion of glutathione due to PMCol exposure ultimately results in a maladaptive response, increasing the consumption of hepatic dietary antioxidants and resulting in elevated reactive oxygen species levels associated with hepatocellular damage and deficits in liver function.

Ablation of the locus coeruleus increases oxidative stress in tg-2576 transgenic but not wild-type mice

Mice transgenic for production of excessive or mutant forms of beta-amyloid differ from patients with Alzheimer's disease in the degree of inflammation, oxidative damage, and alteration of intermediary metabolism, as well as the paucity or absence of neuronal atrophy and cognitive impairment. Previous observers have suggested that differences in inflammatory response reflect a discrepancy in the state of the locus coeruleus (LC), loss of which is an early change in Alzheimer's disease but which is preserved in the transgenic mice. In this paper, we extend these observations by examining the effects of the LC on markers of oxidative stress and intermediary metabolism. We compare four groups: wild-type or Tg2576 Aβ transgenic mice injected with DSP4 or vehicle. Of greatest interest were metabolites different between ablated and intact transgenics, but not between ablated and intact wild-type animals. The Tg2576_DSP4 mice were distinguished from the other three groups by oxidative stress and altered energy metabolism. These observations provide further support for the hypothesis that Tg2576 Aβ transgenic mice with this ablation may be a more congruent model of Alzheimer's disease than are transgenics with an intact LC.

Metabolomic profiling reveals biochemical pathways and biomarkers associated with pathogenesis in cystic fibrosis cells

Cystic fibrosis (CF) is a life-shortening disease caused by a mutation in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. To gain an understanding of the epithelial dysfunction associated with CF mutations and discover biomarkers for therapeutics development, untargeted metabolomic analysis was performed on primary human airway epithelial cell cultures from three separate cohorts of CF patients and non-CF subjects. Statistical analysis revealed a set of reproducible and significant metabolic differences between the CF and non-CF cells. Aside from changes that were consistent with known CF effects, such as diminished cellular regulation against oxidative stress and osmotic stress, new observations on the cellular metabolism in the disease were generated. In the CF cells, the levels of various purine nucleotides, which may function to regulate cellular responses via purinergic signaling, were significantly decreased. Furthermore, CF cells exhibited reduced glucose metabolism in glycolysis, pentose phosphate pathway, and sorbitol pathway, which may further exacerbate oxidative stress and limit the epithelial cell response to environmental pressure. Taken together, these findings reveal novel metabolic abnormalities associated with the CF pathological process and identify a panel of potential biomarkers for therapeutic development using this model system.